关键词: 蚁群算法, 削减-累加双策略, 网络重构, 动态自适应, 信息素

Abstract: Network reconstruction of the power grid is a nonlinear combination optimization problem. With the rapid development of smart grid and the sharp expansion of grid scale, computational complexity of the network reconstruction algorithm increases significantly. Ant colony algorithm has been widely used in solving the combinatorial optimization problem because of its robustness, parallelism and positive feedback mechanism. However, the existing work suffers from the slow computation speed and easily falls into the local optimum. In order to solve the above mentioned problems, this paper proposes a reduction-accumulation dual strategy based ant colony algorithm for network reconfiguration of the power system. On one hand, by defining a reduction factor, number of the ants can decrease continuously given the convergence stability in the iterative process. It implements a dynamically adaptive mechanism in selecting ant number and speeds up the computation. On the other hand, the algorithm defines an accumulation factor and increases a stage of pheromone accumulation. This can guide the algorithm to jump out of the local optimal and improve the probability of finding the optimal topology. With the same numbers of updated pheromone and initial ants, the experimental results show that the proposed algorithm can improve the computation speed by about 25% and reduce the minimum net loss by about 9%, compared with the existing work.

Key words: ant colony algorithm, reduction-accumulation dual strategy, network reconfiguration, dynamic adaptation, pheromone